Payroll data, Sampling error and Equity's inequity

The superstar data release of the month is out, it is the NFP data which gets published every first Friday of the month at 8:30 am in US (EST). The report is prepared by the BLS or Bureau of Labor Statistics which conducts two different surveys?every month to piece together the report. First is the Household survey and second is the Establishment survey. Household survey is a sample survey of 60k households whereas Establishment survey covers around 144k businesses and govt agencies.?

One trivial detail to keep in mind is that these are sample surveys results of which are extrapolated for the entire population to get the economy wide figures. Hence the results can carry some inherent inconsistencies or errors. The primary error can be that the sample is not representative of the population. Though constant efforts are made to correct the same. Statistics tools tell us that the data is reliable and it can be said with 90% confidence that the final population numbers will not differ from the sample estimates by 1.6 standard error. NFP headline number total expected error at 90% confidence is 110k. So if this time the headline data has come as 531k, we can say with 90% confidence that it will be 531K?+ - 110k. The market consensus estimate was 450k, so market was not essentially wrong.

Why I took so much time on the story behind the numbers is to make clear the inherent uncertainty behind any hard numbers. The market however is beyond all these nuances and would treat anything above the consensus as a positive surprise. The US stocks are up again with Dow closing at ATH (again). Improving labor market conditions with continued liquidity support creates a heady cocktail for the stock markets. As per a slightly dated (2016) US govt data only 14% of the US households are directly invested in individual stocks but close to 52% have some kind of stock exposure owing to their retirement accounts like 401Ks. With the Robinhood frenzy of recent times it is very well possible that the latest figure might have shown an uptrend.?

But just for discussion sake a neat 48% of the families are completely out of this?market led wealth creation. With savings returning a negative real return half of the population would have experienced an erosion in their wealth. The comparable stock exposure figures in India and China are 3.7% and 12.1% respectively. Veracity of the numbers apart this reflects the inherent inequitable nature of whole setup and gives us a perspective on how skewed our understanding of the wealth effect is. Wealth is getting generated but in a narrow segment.?

Coming back to the job report, Fed chief said that the Fed is watching the job market keenly and not only the unemployment number but a host of other numbers also. We had written previously that BLS publishes 6 different unemployment measures from U1 to U6. The most headline grabbing is the U3 which is total unemployed as a percent of the civilian labor force, this number came at 4.6% for the month of October. The other numbers from U1 to U6 carry their own nuances and no one can pinpoint which one is the favored measure for FOMC. But one thing is sure that there is a tradeoff between inflation and maximum employment, if you keep monetary conditions too accommodative for too long so that the businesses expand and create jobs for whosoever is looking out, there is a price to pay. Readers would remember the concept of NAIRU (Non accelerating inflation rate of unemployment), this is the mythical rate at which the economy works at magical equilibrium. But as with most of the things in economics this rate is also clear only in hindsight.?

For the weekend read apart from the NFP report on the BLS website, I would recommend a Tim Harford book How to make the World Add Up. It might not make you a star trader but will surely add to your understanding whenever next time any data release comes out so that the right questions are asked (answers notwithstanding).